Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating
Abstract Physical reservoirs are a promising approach for realizing high‐performance artificial intelligence devices utilizing physical devices. Although nonlinear interfered spin‐wave multi‐detection exhibits high nonlinearity and the ability to map in high dimensional feature space, it does not ha...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202411777 |
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| author | Wataru Namiki Daiki Nishioka Yuki Nomura Takashi Tsuchiya Kazuo Yamamoto Kazuya Terabe |
| author_facet | Wataru Namiki Daiki Nishioka Yuki Nomura Takashi Tsuchiya Kazuo Yamamoto Kazuya Terabe |
| author_sort | Wataru Namiki |
| collection | DOAJ |
| description | Abstract Physical reservoirs are a promising approach for realizing high‐performance artificial intelligence devices utilizing physical devices. Although nonlinear interfered spin‐wave multi‐detection exhibits high nonlinearity and the ability to map in high dimensional feature space, it does not have sufficient performance to process time‐series data precisely. Herein, development of an iono–magnonic reservoir by combining such interfered spin wave multi‐detection and ion‐gating involving protonation‐induced redox reaction triggered by the application of voltage is reported. This study is the first to report the manipulation of the propagating spin wave property by ion‐gating and the application of the same to physical reservoir computing. The subject iono–magnonic reservoir can generate various reservoir states in a single homogenous medium by utilizing a spin wave property modulated by ion‐gating. Utilizing the strong nonlinearity resulting from chaos, the reservoir shows good computational performance in completing the Mackey–Glass chaotic time‐series prediction task, and the performance is comparable to that exhibited by simulated neural networks. |
| format | Article |
| id | doaj-art-3e88f79f7f514b7682ff072ed5c60881 |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-3e88f79f7f514b7682ff072ed5c608812025-01-20T13:04:18ZengWileyAdvanced Science2198-38442025-01-01123n/an/a10.1002/advs.202411777Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐GatingWataru Namiki0Daiki Nishioka1Yuki Nomura2Takashi Tsuchiya3Kazuo Yamamoto4Kazuya Terabe5Research Center for Materials Nanoarchitectonics (MANA) National Institute for Materials Science 1‐1 Namiki Tsukuba Ibaraki 305‐0044 JapanResearch Center for Materials Nanoarchitectonics (MANA) National Institute for Materials Science 1‐1 Namiki Tsukuba Ibaraki 305‐0044 JapanNanostructures Research Laboratory Japan Fine Ceramics Center 2‐4‐1 Mutsuno, Atsuta Nagoya Aichi 456‐8587 JapanResearch Center for Materials Nanoarchitectonics (MANA) National Institute for Materials Science 1‐1 Namiki Tsukuba Ibaraki 305‐0044 JapanNanostructures Research Laboratory Japan Fine Ceramics Center 2‐4‐1 Mutsuno, Atsuta Nagoya Aichi 456‐8587 JapanResearch Center for Materials Nanoarchitectonics (MANA) National Institute for Materials Science 1‐1 Namiki Tsukuba Ibaraki 305‐0044 JapanAbstract Physical reservoirs are a promising approach for realizing high‐performance artificial intelligence devices utilizing physical devices. Although nonlinear interfered spin‐wave multi‐detection exhibits high nonlinearity and the ability to map in high dimensional feature space, it does not have sufficient performance to process time‐series data precisely. Herein, development of an iono–magnonic reservoir by combining such interfered spin wave multi‐detection and ion‐gating involving protonation‐induced redox reaction triggered by the application of voltage is reported. This study is the first to report the manipulation of the propagating spin wave property by ion‐gating and the application of the same to physical reservoir computing. The subject iono–magnonic reservoir can generate various reservoir states in a single homogenous medium by utilizing a spin wave property modulated by ion‐gating. Utilizing the strong nonlinearity resulting from chaos, the reservoir shows good computational performance in completing the Mackey–Glass chaotic time‐series prediction task, and the performance is comparable to that exhibited by simulated neural networks.https://doi.org/10.1002/advs.202411777nonlinear interferenceprotonredoxreservoir computingsolid‐state electrolytespin wave |
| spellingShingle | Wataru Namiki Daiki Nishioka Yuki Nomura Takashi Tsuchiya Kazuo Yamamoto Kazuya Terabe Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating Advanced Science nonlinear interference proton redox reservoir computing solid‐state electrolyte spin wave |
| title | Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating |
| title_full | Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating |
| title_fullStr | Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating |
| title_full_unstemmed | Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating |
| title_short | Iono–Magnonic Reservoir Computing With Chaotic Spin Wave Interference Manipulated by Ion‐Gating |
| title_sort | iono magnonic reservoir computing with chaotic spin wave interference manipulated by ion gating |
| topic | nonlinear interference proton redox reservoir computing solid‐state electrolyte spin wave |
| url | https://doi.org/10.1002/advs.202411777 |
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